[{"data":1,"prerenderedAt":195},["ShallowReactive",2],{"svc-detail-ai-integration":3,"sub-work-ai-integration":151,"ill-services\u002Fai-integration":194},{"slug":4,"short":5,"title":6,"tagline":7,"answer":8,"summary":9,"icon":10,"subServices":11,"useCases":57,"benefits":73,"process":79,"tools":92,"integrations":107,"industries":117,"faq":124,"relatedWork":140,"relatedServices":143,"seo":148},"ai-integration","AI Integration","AI Integration Services","OpenAI, Claude and Gemini wired into your product, properly.","AI integration services connect models from OpenAI, Anthropic Claude, Google Gemini and open-source providers into your existing software: SaaS products, backends, mobile apps and internal tools. We build the API orchestration, middleware, SDKs and pipelines that make AI features reliable, secure and cost-controlled, for product and engineering teams that want AI in production, not in a demo.","OpenAI API, Claude and Gemini integration, AI middleware and microservices, SDK development, backend AI pipelines and cloud architecture, so AI features are reliable, observable and cheap to run.","code",[12,17,21,25,29,33,37,41,45,49,53],{"slug":13,"name":14,"text":15,"page":16},"openai-api-integration","OpenAI API integration","GPT, embeddings, Realtime and vision APIs integrated into your product with streaming, function calling, caching and cost controls.",true,{"slug":18,"name":19,"text":20,"page":16},"claude-integration","Claude integration","Anthropic Claude integrated for long-context reasoning, agents, tool use and document workflows, including Bedrock and Vertex deployments.",{"slug":22,"name":23,"text":24},"gemini-integration","Gemini integration","Google Gemini and Vertex AI integration for multimodal, long-context and Google-Cloud-native applications.",{"slug":26,"name":27,"text":28},"ai-into-saas-products","AI into SaaS products","Add assistants, summarisation, search and automation features to your SaaS with tenancy, permissions and billing handled.",{"slug":30,"name":31,"text":32},"ai-api-orchestration","AI API orchestration","Route between providers by cost, latency and quality with retries, fallbacks and evaluation.",{"slug":34,"name":35,"text":36},"ai-middleware","AI middleware & gateways","A single internal gateway for prompts, keys, rate limits, logging, PII redaction and spend.",{"slug":38,"name":39,"text":40},"ai-sdk-development","AI SDK development","Client libraries and internal SDKs so your developers use AI features consistently and safely.",{"slug":42,"name":43,"text":44},"backend-ai-pipelines","Backend AI pipelines","Queues, workers and batch jobs for embedding, classification and generation at volume.",{"slug":46,"name":47,"text":48},"ai-microservices","AI microservices","Containerised, independently deployable AI services with clear contracts and observability.",{"slug":50,"name":51,"text":52},"ai-cloud-architecture","AI cloud architecture","AWS, Azure and GCP designs for AI workloads: networking, secrets, GPUs, cost governance and compliance.",{"slug":54,"name":55,"text":56},"legacy-system-ai-integration","Legacy system AI integration","Bring AI to ERPs, on-prem databases and older systems through adapters and safe write-backs.",[58,61,64,67,70],{"title":59,"text":60},"Ship an AI feature in your SaaS","Add drafting, summarisation or Q&A to your product with proper tenancy, limits and billing.",{"title":62,"text":63},"Consolidate AI usage","Put every team behind one gateway with keys, logging, redaction and spend visibility.",{"title":65,"text":66},"Multi-provider resilience","Route between OpenAI, Claude and Gemini with fallbacks so outages and price changes do not hurt you.",{"title":68,"text":69},"Process at volume","Embed, classify or generate over millions of records with queues and batch APIs.",{"title":71,"text":72},"AI for legacy systems","Expose old systems to AI safely through adapters and approval steps.",[74,75,76,77,78],"AI features that behave in production, not just demos","Predictable token spend and latency","Provider switching as a configuration change","Security, logging and PII controls in one place","Faster delivery of every subsequent feature",[80,83,86,89],{"step":81,"text":82},"Architecture review","Understand your stack, data flows, security requirements and where AI calls will live.",{"step":84,"text":85},"Integration design","Choose providers, define contracts, error handling, streaming, caching and cost limits.",{"step":87,"text":88},"Build and test","Implement services, SDKs or middleware with tests, evaluation cases and load testing.",{"step":90,"text":91},"Observability and rollout","Tracing, cost dashboards and feature flags, then staged release to users.",[93,94,95,96,97,98,99,100,101,102,103,104,105,106],"OpenAI","Anthropic Claude","Google Gemini","AWS Bedrock","Vertex AI","Azure OpenAI","LangChain","LangSmith","FastAPI","Node.js","TypeScript","Redis","Docker","Kubernetes",[108,109,110,111,112,113,114,115,116],"Stripe","Salesforce","HubSpot","Zendesk","Slack","Microsoft 365","Google Workspace","SAP","Odoo",[118,119,120,121,122,123],"saas-technology","finance","retail-ecommerce","healthcare","professional-services","logistics",[125,128,131,134,137],{"q":126,"a":127},"OpenAI, Claude or Gemini: which should we integrate?","Each leads on different tasks and prices move often, so we recommend integrating through a thin abstraction and choosing per feature by testing on your data. Claude is strong on long documents and agents, OpenAI on breadth and Realtime voice, Gemini on multimodal and Google Cloud fit. Most clients end up using two.",{"q":129,"a":130},"How do you keep API costs under control?","Caching, smaller models for simple steps, prompt trimming, batch APIs for offline work, per-tenant limits and a spend dashboard. We estimate cost during design and set alerts so surprises are caught early rather than on the invoice. Cost per feature and per tenant is visible in a dashboard, so you can price and limit usage with real numbers rather than estimates.",{"q":132,"a":133},"Can you integrate AI into our existing codebase?","Yes. We work in Python, Node and TypeScript primarily and adapt to your framework and conventions. Integrations are delivered as reviewed pull requests, services or SDKs, with tests and documentation, so your engineers own them afterwards. We start with a short architecture review so integrations follow your patterns for auth, logging and deployment instead of introducing a parallel stack.",{"q":135,"a":136},"How do you handle security and compliance?","Keys in a secrets manager, a gateway that logs and redacts PII, no-training data agreements or private endpoints such as Bedrock and Azure OpenAI, and audit trails. We document the data flow so security reviews are quick. Where an enterprise customer requires it, we can route their traffic through a dedicated regional endpoint or a private model without changing application code.",{"q":138,"a":139},"What about rate limits and outages?","We build with retries, back-off, queues and provider fallbacks, and test failure modes deliberately. Critical paths degrade gracefully, to a cached answer or a human route, instead of failing silently. Load tests against provider limits are part of delivery, so you know your real ceiling before a launch or campaign finds it for you.",[141,142],"saas-onboarding-assistant","ecommerce-personalisation-plugin",[144,145,146,147],"generative-ai-llm","ai-saas-product-development","mlops-ai-infrastructure","ai-agents",{"title":149,"description":150},"AI Integration: OpenAI, Claude & Gemini APIs | AIYatch","AI integration services: OpenAI API, Claude and Gemini integration, AI middleware, SDKs, backend pipelines and microservices built for production.",[152,167,180],{"path":153,"title":154,"description":155,"industry":156,"services":157,"results":159,"cover":166,"coverAlt":166},"\u002Fwork\u002Fenterprise-rag-knowledge-base","RAG knowledge base for an enterprise services firm","A retrieval-augmented assistant over thousands of internal documents, with citations and role-based access.","Professional Services",[158,4,144],"rag-systems",[160,163],{"value":161,"label":162},"~70%","faster answers to policy and process questions",{"value":164,"label":165},"100%","answers with source citations",null,{"path":168,"title":169,"description":170,"industry":156,"services":171,"results":173,"cover":166,"coverAlt":166},"\u002Fwork\u002Fcrm-automation-plugin","AI plugin for CRM automation","An agent inside the client's CRM that enriches leads, drafts follow-ups and updates records from email and call notes.",[147,172,4],"ai-automation",[174,177],{"value":175,"label":176},"10+ hrs","saved per rep per week",{"value":178,"label":179},"-90%","missing CRM fields on new leads",{"path":181,"title":182,"description":183,"industry":184,"services":185,"results":187,"cover":166,"coverAlt":166},"\u002Fwork\u002Fecommerce-personalisation-plugin","Personalisation plugin for an e-commerce platform","Recommendation and search-ranking models packaged as a plugin for the client's storefront.","Retail & E-commerce",[186,4],"data-analytics-predictive-ai",[188,191],{"value":189,"label":190},"+18%","sales from recommended products",{"value":192,"label":193},"\u003C80 ms","recommendation latency","\u003Csvg xmlns=\"http:\u002F\u002Fwww.w3.org\u002F2000\u002Fsvg\" viewBox=\"0 0 640 480\" role=\"img\" aria-hidden=\"true\">\u003Cg fill=\"none\" stroke=\"currentColor\" stroke-width=\"5\" stroke-linecap=\"round\" stroke-linejoin=\"round\">\u003Crect x=\"66\" y=\"200\" width=\"60\" height=\"60\" rx=\"6\"\u002F>\u003Crect x=\"82.8\" y=\"216.8\" width=\"26.4\" height=\"26.4\" rx=\"3\" stroke-opacity=\"0.45\"\u002F>\u003Cline x1=\"81\" y1=\"200\" x2=\"81\" y2=\"192\"\u002F>\u003Cline x1=\"81\" y1=\"260\" x2=\"81\" y2=\"268\"\u002F>\u003Cline x1=\"66\" y1=\"215\" x2=\"58\" y2=\"215\"\u002F>\u003Cline x1=\"126\" y1=\"215\" x2=\"134\" y2=\"215\"\u002F>\u003Cline x1=\"96\" y1=\"200\" x2=\"96\" y2=\"192\"\u002F>\u003Cline x1=\"96\" y1=\"260\" x2=\"96\" y2=\"268\"\u002F>\u003Cline x1=\"66\" y1=\"230\" x2=\"58\" y2=\"230\"\u002F>\u003Cline x1=\"126\" y1=\"230\" x2=\"134\" y2=\"230\"\u002F>\u003Cline x1=\"111\" y1=\"200\" x2=\"111\" y2=\"192\"\u002F>\u003Cline x1=\"111\" y1=\"260\" x2=\"111\" y2=\"268\"\u002F>\u003Cline x1=\"66\" y1=\"245\" x2=\"58\" y2=\"245\"\u002F>\u003Cline x1=\"126\" y1=\"245\" x2=\"134\" y2=\"245\"\u002F>\u003Ccircle cx=\"96\" cy=\"230\" r=\"6\" fill=\"var(--accent, #0E7490)\" stroke=\"none\"\u002F>\u003Cpath d=\"M132 230C160 230 150 230 190 230\" stroke-width=\"3.5\"\u002F>\u003Cpath d=\"M190 190A20 20 0 0 1 210 170H270A20 20 0 0 1 290 190V200A16 16 0 0 0 306 216H316V244H306A16 16 0 0 0 290 260V270A20 20 0 0 1 270 290H210A20 20 0 0 1 190 270Z\"\u002F>\u003Cline x1=\"316\" y1=\"216\" x2=\"350\" y2=\"216\"\u002F>\u003Cline x1=\"316\" y1=\"244\" x2=\"350\" y2=\"244\"\u002F>\u003Crect x=\"372\" y=\"150\" width=\"130\" height=\"160\" rx=\"22\"\u002F>\u003Ccircle cx=\"414\" cy=\"216\" r=\"9\" stroke-width=\"3.5\"\u002F>\u003Ccircle cx=\"414\" cy=\"244\" r=\"9\" stroke-width=\"3.5\"\u002F>\u003Ccircle cx=\"460\" cy=\"230\" r=\"8\" fill=\"var(--accent, #0E7490)\" stroke=\"none\"\u002F>\u003Cpath d=\"M502 230C525 230 520 230 540 230\" stroke-width=\"3.5\"\u002F>\u003Crect x=\"540\" y=\"170\" width=\"56\" height=\"120\" rx=\"14\" stroke-width=\"3.5\"\u002F>\u003Cline x1=\"560\" y1=\"275\" x2=\"576\" y2=\"275\" stroke-width=\"3.5\"\u002F>\u003C\u002Fg>\u003C\u002Fsvg>",1792973685339]